This work studies the design of MET-LDPC code ensembles at low code rates with good threshold performances and exponentially few small weight codewords. There was a notable study on the condition, so called the ` t-value condition', for exponentially few small weight codewords. Meanwhile, it was shown that by introducing degree-one variable nodes, the threshold performances of MET-LDPC code ensembles of low rates can be significantly improved. However, the degree-one variable nodes may result in small weight codewords and thus must be carefully introduced to MET-LDPC code ensembles. Despite the importance, the existing t-value condition was developed only for MET-LDPC code ensembles without degree-one variable nodes. This work extends the t-value condition to MET-LDPC code ensembles with degree-one variable nodes, which includes the existing work as a special case. The extended t-value condition provides useful insights into the contributions of degree-one variable nodes to the distribution of small weight codewords. Thus, the results of this work allow us to design MET-LDPC code ensembles of low rates with both good threshold performances and exponentially few small weight codewords. In addition, it will be demonstrated that MET-LDPC codes at finite lengths based on the designed code ensembles have good error-rate performances both in the waterfall and low-error-rate regions.
This work studies the design of MET-LDPC code ensembles at low code rates with good threshold performances and exponentially few small weight codewords. There was a notable study on the condition, so called the ` t-value condition', for exponentially few small weight codewords. Meanwhile, it was shown that by introducing degree-one variable nodes, the threshold performances of MET-LDPC code ensembles of low rates can be significantly improved. However, the degree-one variable nodes may result in small weight codewords and thus must be carefully introduced to MET-LDPC code ensembles. Despite the importance, the existing t-value condition was developed only for MET-LDPC code ensembles without degree-one variable nodes. This work extends the t-value condition to MET-LDPC code ensembles with degree-one variable nodes, which includes the existing work as a special case. The extended t-value condition provides useful insights into the contributions of degree-one variable nodes to the distribution of small weight codewords. Thus, the results of this work allow us to design MET-LDPC code ensembles of low rates with both good threshold performances and exponentially few small weight codewords. In addition, it will be demonstrated that MET-LDPC codes at finite lengths based on the designed code ensembles have good error-rate performances both in the waterfall and low-error-rate regions.
Multi-edge type LDPC codes are introduced by Richardson and Urbanke, and they show examples of their ensembles have better performance than other known ensembles. Orlitsky et al. derived the condition for irregular LDPC code ensembles with minimum distance linearly increasing in code length. Nakasendo et al. derived the condition that code ensembles have exponentially decreasing small linear weight codewords for two-edge type LDPC code ensembles which is simple example of multi-edge type LDPC code ensembles. In this paper, we derive the condition for three-edge type LDPC code ensembles whose edge-types does not share any variable node and does share all of the check nodes with exponentially decreasing small linear weight codewords. The condition is necessary for the existence of the average relative minimum distance of ensembles. Our method is expected to derive the condition for multi-edge type LDPC codes.
This paper addresses the issue of design of low-rate sparse-graph codes with linear minimum distance in the blocklength. First, we define a necessary condition which needs to be satisfied when the linear minimum distance is to be ensured. The condition is formulated in terms of degree-1 and degree-2 variable nodes and of low-weight codewords of the underlying code, and it generalizies results known for turbo codes [8] and LDPC codes. Then, we present a new ensemble of low-rate codes, which itself is a subclass of TLDPC codes [4], [5], and which is designed under this necessary condition. The asymptotic analysis of the ensemble shows that its iterative threshold is situated close to the Shannon limit. In addition to the linear minimum distance property, it has a simple structure and enjoys a low decoding complexity and a fast convergence.
For a (lambda(x); rho(x)) standard irregular LDPC code ensemble, the growth rate of the average weight distribution for small relative weight omega is given by log(lambda'(0)rho'(1))omega + O(omega2) in the limit of code length n. If lambda'(0)rho'(1) < 1, there exist exponentially few code words of small linear weight, as n tends to infinity. It is known that the condition coincides with the stability condition of density evolution over the erasure channels with the erasure probability 1. In this paper, we show that this is also the case with multi-edge type LDPC (MET-LDPC) codes. MET-LDPC codes are generalized structured LDPC codes introduced by Richardson and Urbanke. The parameter corresponding lambda'(0)rho'(1) appearing in the conditions for MET-LDPC codes is given by the spectral radius of the matrix defined by extended degree distributions.
Low-density parity-check (LDPC) codes can approach the Shannon limit performance closely, and are becoming one of the most promising channel codes in the Error Control Coding area.The performance of an LDPC code with given length is mainly affected by the sizes of some combinatorial characteristics of its corresponding bipartite graph and the distribution of variable degrees and check node degrees.With the help of the density evolution algorithm, randomly designed LDPC codes, with carefully chosen degree distribution pairs, have been shown to achieve better Shannon capacity performance than their regular counterparts when decoded using the iterative belief propagation (BP) decoding algorithm.However, regular LDPC codes outperform their irregular counterparts in term of their error floors.Therefore, construction of LDPC codes which have both attractive error rate performance and low error floor performance has become an attractive topic.Currently, optimization of variable node degree distribution and check node degree distribution for an LDPC code with given length, which could help the code to achieve good Shannon limit performance, has been extensively studied.In this dissertation, we demonstrate some approaches of improving the error floor performance for a given LDPC code with desired degree distribution pair.The contribution mainly includes three parts.In the first part, the relationship between cycles and unfavorable combinatorial
This thesis addresses the topic of Low-Density Parity-Check (LDPC) code analysis, both asymptotically and for finite block lengths. Since in general it is a difficult problem to analyze individual code instances, ensemble averages are studied by following Gallager's original idea and results of Luby et al. Often, one can relate the insights gained by studying ensemble averages to statements regarding individual codes by proving that most elements in the ensemble behave "close" to the average. One important such average is the average weight distribution, another is the average pseudo-codeword distribution, where pseudo-codewords play the same role under iterative decoding as codewords do for maximum likelihood decoding. One of the main contributions of this thesis is the calculation of such averages for fully irregular LDPC code ensembles. Much of classical coding theory is aimed at the construction of codes with large minimum distance. This is so since away from capacity accurate bounds on the performance of a code can be given in terms of its minimum distance (or more generally, in terms of its weight distribution). Therefore, it is of interest to investigate what role the minimum distance plays for iteratively decoded LDPC code ensembles. In particular, sequences of capacity-achieving LDPC code ensembles of increasing length when transmission takes place over the Binary Erasure Channel (BEC) are investigated. It is shown that, under certain technical conditions, the minimum distance of such ensembles grows sub-linearly in the block length, a result which is somewhat surprising from a classical point of view. Specific attention is also given to the design of LDPC code ensembles, where an inherent trade-off is observed between achieving large minimum distance (which is relevant for the so called error-floor regime) and achieving a large threshold (which in the limit of long block lengths determines the worst channel on which transmission can be accomplished reliably). Most results on iterative coding systems to date address their asymptotic performance, i.e., their performance when the block length tends to infinity. For small and moderate block lengths the behavior of a code can deviate significantly from its asymptotic limit. It is therefore of high practical value to be able to analyze the finite-length performance of LDPC code ensembles. In this thesis, an exact such analysis is presented for iteratively decoded LDPC code ensembles over the BEC. In particular, expressions for the exact average bit and block erasure probabilities are computed by solving a set of recursions. Such an analysis is the starting point for a finite-length optimization, a topic which is slated for future work. The methods used in this thesis include a combinatorial approach (familiar to the coding society) as well as the powerful techniques developed in the statistical physics community, for example, the replica method or the mean-field approximation. Although the statistical physics techniques are ideally suited for the analysis of iterative coding systems, they are to date only accessible to a relatively small community. Therefore, an overview of these techniques is first presented using a language familiar to the coding theory community. Next, in order to highlight the differences and common points between the combinatorial and the statistical physics approaches, both techniques are applied to the weight distribution problem. It turns out that for regular ensembles, both methods yield the same result, while for irregular ensembles, they do differ in general.
Multi-edge type LDPC codes are introduced by Richardson and Urbanke, and they show examples of their ensembles have better performance than other known ensembles. Orlitsky et al. derived the condition for irregular LDPC code ensembles with small linear weight codewords exponentially decreasing in code length. Nakasendo et al. derived the condition in which code ensembles have exponentially decreasing small linear weight codewords for two-edge type LDPC code ensembles which is simple example of multi-edge type LDPC code ensembles. Our conclusion is the same as that of Nakasendo et al., and although Nakasendopsilas method is difficult to apply to more than three edge-types, there is a possibility that our method using Hayman approximation as Di et al. do derives the condition for multi-edge type LDPC codes ensembles.